GradePilot should not sound like a generic AI grader. Its strongest promise is a repeatable academic marking workspace where the brief, rubric, submission, integrity step, and final tutor approval stay connected.
Built for academic trust
GradePilot keeps AI assistance inside a tutor-led marking workflow.
The product direction is intentionally focused: help tutors and lecturers move faster without losing control of rubrics, judgement, integrity review, or final feedback.
1
Human final control
AI helps draft and structure feedback, but the educator owns the final mark and written response.
2
Reusable setup
Subjects, rubrics, penalty rules, and feedback patterns become easier to reuse across future teaching cycles.
3
Workflow over chat
The experience should feel calmer and more auditable than copying academic work into separate AI tools.
What the product should become
Phase 1
Lead capture and clear demo flow
Use the current website to explain the value, collect early users, and show a credible dashboard preview.
Phase 2
Upload, rubric, and feedback workflow
Connect assignment briefs, rubrics, and submissions into one guided flow with editable first-pass feedback.
Phase 3
Integrity and team controls
Add review checkpoints, saved subject rules, role access, and reporting for tutors, lecturers, and coordinators.
Start with one assignment, then make the workflow reusable.
That is the adoption path GradePilot should keep selling.